Pandas Profiling Report

Dataset statistics

Number of variables	18
Number of observations	1274
Missing cells	2330
Missing cells (%)	10.2%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	179.3 KiB
Average record size in memory	144.1 B

Variable types

Numeric	12
Categorical	6

Alerts

`City_Mileage` has constant value "12.7"	Constant
`Ex-Showroom_Price` is highly correlated with `Displacement` and 5 other fields	High correlation
`Displacement` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Cylinders` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Fuel_Tank_Capacity` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Height` is highly correlated with `Doors` and 1 other fields	High correlation
`Length` is highly correlated with `Ex-Showroom_Price` and 6 other fields	High correlation
`Width` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Doors` is highly correlated with `Height`	High correlation
`Gears` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Seating_Capacity` is highly correlated with `Height`	High correlation
`Boot_Space` is highly correlated with `Length`	High correlation
`Diesel` is highly correlated with `Petrol`	High correlation
`Petrol` is highly correlated with `Diesel`	High correlation
`Ex-Showroom_Price` is highly correlated with `Displacement` and 2 other fields	High correlation
`Displacement` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Cylinders` is highly correlated with `Ex-Showroom_Price` and 6 other fields	High correlation
`Fuel_Tank_Capacity` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Height` is highly correlated with `Doors` and 1 other fields	High correlation
`Length` is highly correlated with `Displacement` and 4 other fields	High correlation
`Width` is highly correlated with `Displacement` and 4 other fields	High correlation
`Doors` is highly correlated with `Cylinders` and 2 other fields	High correlation
`Gears` is highly correlated with `Displacement` and 4 other fields	High correlation
`Seating_Capacity` is highly correlated with `Height` and 1 other fields	High correlation
`Diesel` is highly correlated with `Petrol`	High correlation
`Petrol` is highly correlated with `Diesel`	High correlation
`Ex-Showroom_Price` is highly correlated with `Displacement` and 5 other fields	High correlation
`Displacement` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Cylinders` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Fuel_Tank_Capacity` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Height` is highly correlated with `Doors` and 1 other fields	High correlation
`Length` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Width` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Doors` is highly correlated with `Height`	High correlation
`Gears` is highly correlated with `Ex-Showroom_Price` and 5 other fields	High correlation
`Seating_Capacity` is highly correlated with `Height`	High correlation
`Diesel` is highly correlated with `Petrol`	High correlation
`Petrol` is highly correlated with `Diesel`	High correlation
`Diesel` is highly correlated with `Petrol`	High correlation
`Petrol` is highly correlated with `Diesel`	High correlation
`Ex-Showroom_Price` is highly correlated with `Displacement` and 4 other fields	High correlation
`Displacement` is highly correlated with `Ex-Showroom_Price` and 9 other fields	High correlation
`Cylinders` is highly correlated with `Ex-Showroom_Price` and 7 other fields	High correlation
`Fuel_Tank_Capacity` is highly correlated with `Ex-Showroom_Price` and 6 other fields	High correlation
`Height` is highly correlated with `Ex-Showroom_Price` and 6 other fields	High correlation
`Length` is highly correlated with `Ex-Showroom_Price` and 6 other fields	High correlation
`Width` is highly correlated with `Displacement` and 4 other fields	High correlation
`Doors` is highly correlated with `Displacement` and 4 other fields	High correlation
`Gears` is highly correlated with `Displacement` and 5 other fields	High correlation
`Seating_Capacity` is highly correlated with `Displacement` and 4 other fields	High correlation
`Basic_Warranty` is highly correlated with `Displacement` and 2 other fields	High correlation
`Boot_Space` is highly correlated with `Fuel_Tank_Capacity` and 2 other fields	High correlation
`Diesel` is highly correlated with `Petrol`	High correlation
`Petrol` is highly correlated with `Diesel`	High correlation
`Electric` is highly correlated with `Basic_Warranty`	High correlation
`Cylinders` has 65 (5.1%) missing values	Missing
`Valves_Per_Cylinder` has 101 (7.9%) missing values	Missing
`Fuel_Tank_Capacity` has 67 (5.3%) missing values	Missing
`City_Mileage` has 1273 (99.9%) missing values	Missing
`Gears` has 105 (8.2%) missing values	Missing
`Basic_Warranty` has 438 (34.4%) missing values	Missing
`Boot_Space` has 247 (19.4%) missing values	Missing

Reproduction

Analysis started	2022-05-27 06:08:43.908414
Analysis finished	2022-05-27 06:09:31.423813
Duration	47.52 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

Ex-Showroom_Price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	1177
Distinct (%)	92.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4435365.062

Minimum	236447
Maximum	192142937
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	236447
5-th percentile	467468.8
Q1	743628
median	1059871
Q3	2973250
95-th percentile	21463405.8
Maximum	192142937
Range	191906490
Interquartile range (IQR)	2229622

Descriptive statistics

Standard deviation	10673243.47
Coefficient of variation (CV)	2.406395714
Kurtosis	88.82592216
Mean	4435365.062
Median Absolute Deviation (MAD)	468772
Skewness	7.230684434
Sum	5650655089
Variance	1.139181262 × 10¹⁴
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
999900	14	1.1%
999990	4	0.3%
989000	3	0.2%
925000	3	0.2%
745000	3	0.2%
3830000	2	0.2%
3233000	2	0.2%
3420000	2	0.2%
52000000	2	0.2%
6440000	2	0.2%
Other values (1167)	1237	97.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
236447	1	0.1%
263000	1	0.1%
272223	1	0.1%
279650	1	0.1%
282778	1	0.1%
283000	1	0.1%
283290	1	0.1%
284485	1	0.1%
292667	1	0.1%
294800	1	0.1%

Value	Count	Frequency (%)
192142937	1	0.1%
95000000	1	0.1%
83755383	1	0.1%
77312661	1	0.1%
75400000	1	0.1%
69500000	1	0.1%
59216193	1	0.1%
53247201	1	0.1%
53210327	1	0.1%
52571294	1	0.1%

Displacement
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	129
Distinct (%)	10.2%
Missing	11
Missing (%)	0.9%
Infinite	0
Infinite (%)	0.0%
Mean	1853.947743

Minimum	72
Maximum	7993
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	72
5-th percentile	998
Q1	1198
median	1497
Q3	1998
95-th percentile	3996
Maximum	7993
Range	7921
Interquartile range (IQR)	800

Descriptive statistics

Standard deviation	1049.451565
Coefficient of variation (CV)	0.5660631852
Kurtosis	7.390867627
Mean	1853.947743
Median Absolute Deviation (MAD)	301
Skewness	2.508613718
Sum	2341536
Variance	1101348.587
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1197	108	8.5%
1498	87	6.8%
1248	62	4.9%
1198	58	4.6%
1497	56	4.4%
998	53	4.2%
2179	46	3.6%
1199	39	3.1%
1461	38	3.0%
1968	29	2.3%
Other values (119)	687	53.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
72	3	0.2%
216	2	0.2%
624	6	0.5%
796	12	0.9%
799	8	0.6%
998	53	4.2%
999	20	1.6%
1047	1	0.1%
1086	8	0.6%
1120	5	0.4%

Value	Count	Frequency (%)
7993	1	0.1%
6752	1	0.1%
6750	1	0.1%
6749	4	0.3%
6598	1	0.1%
6593	1	0.1%
6592	3	0.2%
6498	3	0.2%
6496	1	0.1%
6417	1	0.1%

Cylinders
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	9
Distinct (%)	0.7%
Missing	65
Missing (%)	5.1%
Infinite	0
Infinite (%)	0.0%
Mean	4.371381307

Minimum	2
Maximum	16
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	2
5-th percentile	3
Q1	4
median	4
Q3	4
95-th percentile	8
Maximum	16
Range	14
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.627640441
Coefficient of variation (CV)	0.3723400744
Kurtosis	10.07180002
Mean	4.371381307
Median Absolute Deviation (MAD)	0
Skewness	2.884777547
Sum	5285
Variance	2.649213405
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
4	789	61.9%
3	213	16.7%
6	106	8.3%
8	53	4.2%
12	21	1.6%
5	10	0.8%
10	10	0.8%
2	6	0.5%
16	1	0.1%
(Missing)	65	5.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	6	0.5%
3	213	16.7%
4	789	61.9%
5	10	0.8%
6	106	8.3%
8	53	4.2%
10	10	0.8%
12	21	1.6%
16	1	0.1%

Value	Count	Frequency (%)
16	1	0.1%
12	21	1.6%
10	10	0.8%
8	53	4.2%
6	106	8.3%
5	10	0.8%
4	789	61.9%
3	213	16.7%
2	6	0.5%

Valves_Per_Cylinder
Real number (ℝ_≥0)

MISSING

Distinct	8
Distinct (%)	0.7%
Missing	101
Missing (%)	7.9%
Infinite	0
Infinite (%)	0.0%
Mean	3.977834612

Minimum	1
Maximum	16
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	1
5-th percentile	4
Q1	4
median	4
Q3	4
95-th percentile	4
Maximum	16
Range	15
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.8341187027
Coefficient of variation (CV)	0.2096916499
Kurtosis	103.7751373
Mean	3.977834612
Median Absolute Deviation (MAD)	0
Skewness	7.950267485
Sum	4666
Variance	0.6957540102
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
4	1112	87.3%
2	46	3.6%
12	4	0.3%
8	4	0.3%
16	2	0.2%
1	2	0.2%
3	2	0.2%
6	1	0.1%
(Missing)	101	7.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	2	0.2%
2	46	3.6%
3	2	0.2%
4	1112	87.3%
6	1	0.1%
8	4	0.3%
12	4	0.3%
16	2	0.2%

Value	Count	Frequency (%)
16	2	0.2%
12	4	0.3%
8	4	0.3%
6	1	0.1%
4	1112	87.3%
3	2	0.2%
2	46	3.6%
1	2	0.2%

Fuel_Tank_Capacity
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	63
Distinct (%)	5.2%
Missing	67
Missing (%)	5.3%
Infinite	0
Infinite (%)	0.0%
Mean	52.11922121

Minimum	15
Maximum	105
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	15
5-th percentile	35
Q1	40
median	46
Q3	60
95-th percentile	86
Maximum	105
Range	90
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	16.45895579
Coefficient of variation (CV)	0.3157943539
Kurtosis	0.316968109
Mean	52.11922121
Median Absolute Deviation (MAD)	9
Skewness	0.9371756109
Sum	62907.9
Variance	270.8972256
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
45	125	9.8%
35	124	9.7%
50	94	7.4%
60	91	7.1%
37	79	6.2%
55	73	5.7%
40	56	4.4%
42	51	4.0%
70	48	3.8%
44	48	3.8%
Other values (53)	418	32.8%
(Missing)	67	5.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
15	1	0.1%
24	5	0.4%
27	10	0.8%
28	18	1.4%
32	21	1.6%
35	124	9.7%
36	1	0.1%
37	79	6.2%
40	56	4.4%
41	14	1.1%

Value	Count	Frequency (%)
105	6	0.5%
100	7	0.5%
96	1	0.1%
93.5	4	0.3%
93	7	0.5%
92	2	0.2%
91	2	0.2%
90.5	1	0.1%
90	21	1.6%
89	4	0.3%

Height
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	211
Distinct (%)	16.6%
Missing	1
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%
Mean	1591.408362

Minimum	1.845
Maximum	2670
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	1.845
5-th percentile	1415.6
Q1	1495
median	1557
Q3	1666
95-th percentile	1870
Maximum	2670
Range	2668.155
Interquartile range (IQR)	171

Descriptive statistics

Standard deviation	157.6810887
Coefficient of variation (CV)	0.09908273228
Kurtosis	9.667344133
Mean	1591.408362
Median Absolute Deviation (MAD)	83
Skewness	-0.2381918633
Sum	2025862.845
Variance	24863.32573
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1520	49	3.8%
1510	35	2.7%
1640	33	2.6%
1560	29	2.3%
1525	27	2.1%
1607	27	2.1%
1495	24	1.9%
1655	22	1.7%
1475	22	1.7%
1785	21	1.6%
Other values (201)	984	77.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.845	1	0.1%
1136	3	0.2%
1165	9	0.7%
1200	1	0.1%
1203	1	0.1%
1211	1	0.1%
1212	1	0.1%
1213	2	0.2%
1250	1	0.1%
1252	1	0.1%

Value	Count	Frequency (%)
2670	1	0.1%
2075	2	0.2%
2055	4	0.3%
1995	6	0.5%
1977	2	0.2%
1969	1	0.1%
1938	1	0.1%
1930	4	0.3%
1922	4	0.3%
1910	3	0.2%

Length
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	227
Distinct (%)	17.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4296.781507

Minimum	4.64
Maximum	6092
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	4.64
5-th percentile	3606.5
Q1	3991.25
median	4331
Q3	4620
95-th percentile	5115
Maximum	6092
Range	6087.36
Interquartile range (IQR)	628.75

Descriptive statistics

Standard deviation	476.9256823
Coefficient of variation (CV)	0.1109960284
Kurtosis	4.636160941
Mean	4296.781507
Median Absolute Deviation (MAD)	336
Skewness	-0.3357446246
Sum	5474099.64
Variance	227458.1065
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3995	174	13.7%
4440	36	2.8%
4585	29	2.3%
3700	29	2.3%
3994	27	2.1%
4395	27	2.1%
4315	25	2.0%
3600	20	1.6%
4270	18	1.4%
4413	18	1.4%
Other values (217)	871	68.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4.64	1	0.1%
2752	2	0.2%
3164	6	0.5%
3370	2	0.2%
3390	2	0.2%
3395	1	0.1%
3429	6	0.5%
3430	1	0.1%
3445	8	0.6%
3545	5	0.4%

Value	Count	Frequency (%)
6092	1	0.1%
5842	2	0.2%
5612	1	0.1%
5575	1	0.1%
5569	1	0.1%
5458	1	0.1%
5453	1	0.1%
5399	1	0.1%
5370	1	0.1%
5341	1	0.1%

Width
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	182
Distinct (%)	14.4%
Missing	12
Missing (%)	0.9%
Infinite	0
Infinite (%)	0.0%
Mean	1788.343776

Minimum	1.845
Maximum	2226
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	1.845
5-th percentile	1579.05
Q1	1695
median	1770
Q3	1852
95-th percentile	2091
Maximum	2226
Range	2224.155
Interquartile range (IQR)	157

Descriptive statistics

Standard deviation	150.8881151
Coefficient of variation (CV)	0.08437310382
Kurtosis	16.16251079
Mean	1788.343776
Median Absolute Deviation (MAD)	75
Skewness	-0.6546219165
Sum	2256889.845
Variance	22767.22327
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1695	76	6.0%
1735	70	5.5%
1730	36	2.8%
1811	30	2.4%
1745	29	2.3%
1660	28	2.2%
1699	28	2.2%
1850	25	2.0%
1890	24	1.9%
1818	23	1.8%
Other values (172)	893	70.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.845	1	0.1%
1312	2	0.2%
1410	2	0.2%
1459	1	0.1%
1475	6	0.5%
1490	15	1.2%
1520	10	0.8%
1540	2	0.2%
1560	6	0.5%
1570	6	0.5%

Value	Count	Frequency (%)
2226	1	0.1%
2220	14	1.1%
2218	3	0.2%
2208	1	0.1%
2207	2	0.2%
2200	8	0.6%
2194	2	0.2%
2181	1	0.1%
2175	2	0.2%
2169	4	0.3%

Doors
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.3%
Missing	4
Missing (%)	0.3%
Memory size	10.1 KiB

5.0	835
4.0	362
2.0	61
3.0	12

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	3810
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	5.0
2nd row	5.0
3rd row	4.0
4th row	5.0
5th row	5.0

Common Values

Value	Count	Frequency (%)
5.0	835	65.5%
4.0	362	28.4%
2.0	61	4.8%
3.0	12	0.9%
(Missing)	4	0.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
5.0	835	65.7%
4.0	362	28.5%
2.0	61	4.8%
3.0	12	0.9%

Most occurring characters

Value	Count	Frequency (%)
.	1270	33.3%
0	1270	33.3%
5	835	21.9%
4	362	9.5%
2	61	1.6%
3	12	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2540	66.7%
Other Punctuation	1270	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1270	50.0%
5	835	32.9%
4	362	14.3%
2	61	2.4%
3	12	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	1270	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	3810	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	1270	33.3%
0	1270	33.3%
5	835	21.9%
4	362	9.5%
2	61	1.6%
3	12	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3810	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	1270	33.3%
0	1270	33.3%
5	835	21.9%
4	362	9.5%
2	61	1.6%
3	12	0.3%

City_Mileage
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	100.0%
Missing	1273
Missing (%)	99.9%
Memory size	10.1 KiB

12.7	1

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	4
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	100.0%

Sample

1st row	12.7

Common Values

Value	Count	Frequency (%)
12.7	1	0.1%
(Missing)	1273	99.9%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
12.7	1	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	1	25.0%
2	1	25.0%
.	1	25.0%
7	1	25.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	3	75.0%
Other Punctuation	1	25.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	1	33.3%
2	1	33.3%
7	1	33.3%

Other Punctuation

Value	Count	Frequency (%)
.	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	4	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	1	25.0%
2	1	25.0%
.	1	25.0%
7	1	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	1	25.0%
2	1	25.0%
.	1	25.0%
7	1	25.0%

Gears
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	0.5%
Missing	105
Missing (%)	8.2%
Infinite	0
Infinite (%)	0.0%
Mean	5.879384089

Minimum	4
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	4
5-th percentile	5
Q1	5
median	5
Q3	7
95-th percentile	8
Maximum	9
Range	5
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.1791544
Coefficient of variation (CV)	0.2005574704
Kurtosis	-0.1414491445
Mean	5.879384089
Median Absolute Deviation (MAD)	0
Skewness	0.9973986314
Sum	6873
Variance	1.3904051
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
5	614	48.2%
6	233	18.3%
8	139	10.9%
7	137	10.8%
9	30	2.4%
4	16	1.3%
(Missing)	105	8.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4	16	1.3%
5	614	48.2%
6	233	18.3%
7	137	10.8%
8	139	10.9%
9	30	2.4%

Value	Count	Frequency (%)
9	30	2.4%
8	139	10.9%
7	137	10.8%
6	233	18.3%
5	614	48.2%
4	16	1.3%

Seating_Capacity
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	8
Distinct (%)	0.6%
Missing	6
Missing (%)	0.5%
Infinite	0
Infinite (%)	0.0%
Mean	5.273659306

Minimum	2
Maximum	16
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	2
5-th percentile	4
Q1	5
median	5
Q3	5
95-th percentile	7
Maximum	16
Range	14
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.141884034
Coefficient of variation (CV)	0.2165259392
Kurtosis	8.198445515
Mean	5.273659306
Median Absolute Deviation (MAD)	0
Skewness	1.071815555
Sum	6687
Variance	1.303899148
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
5	915	71.8%
7	183	14.4%
4	69	5.4%
2	38	3.0%
6	26	2.0%
9	19	1.5%
8	17	1.3%
16	1	0.1%
(Missing)	6	0.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	38	3.0%
4	69	5.4%
5	915	71.8%
6	26	2.0%
7	183	14.4%
8	17	1.3%
9	19	1.5%
16	1	0.1%

Value	Count	Frequency (%)
16	1	0.1%
9	19	1.5%
8	17	1.3%
7	183	14.4%
6	26	2.0%
5	915	71.8%
4	69	5.4%
2	38	3.0%

Basic_Warranty
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	0.7%
Missing	438
Missing (%)	34.4%
Infinite	0
Infinite (%)	0.0%
Mean	2.970095694

Minimum	1
Maximum	24
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	2
median	2
Q3	3
95-th percentile	3
Maximum	24
Range	23
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	3.352405945
Coefficient of variation (CV)	1.128719843
Kurtosis	34.37032129
Mean	2.970095694
Median Absolute Deviation (MAD)	0
Skewness	5.925171691
Sum	2483
Variance	11.23862562
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
2	466	36.6%
3	332	26.1%
24	20	1.6%
4	12	0.9%
1	3	0.2%
8	3	0.2%
(Missing)	438	34.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	3	0.2%
2	466	36.6%
3	332	26.1%
4	12	0.9%
8	3	0.2%
24	20	1.6%

Value	Count	Frequency (%)
24	20	1.6%
8	3	0.2%
4	12	0.9%
3	332	26.1%
2	466	36.6%
1	3	0.2%

Boot_Space
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	137
Distinct (%)	13.3%
Missing	247
Missing (%)	19.4%
Infinite	0
Infinite (%)	0.0%
Mean	387.5856865

Minimum	20
Maximum	1761
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.1 KiB

Quantile statistics

Minimum	20
5-th percentile	150
Q1	260
median	375
Q3	475
95-th percentile	615.7
Maximum	1761
Range	1741
Interquartile range (IQR)	215

Descriptive statistics

Standard deviation	179.1006773
Coefficient of variation (CV)	0.4620931152
Kurtosis	14.9780265
Mean	387.5856865
Median Absolute Deviation (MAD)	103
Skewness	2.554735182
Sum	398050.5
Variance	32077.05259
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
350	44	3.5%
475	35	2.7%
460	31	2.4%
510	30	2.4%
251	28	2.2%
420	24	1.9%
256	22	1.7%
243	22	1.7%
400	21	1.6%
235	21	1.6%
Other values (127)	749	58.8%
(Missing)	247	19.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
20	2	0.2%
54	1	0.1%
70	8	0.6%
94	2	0.2%
96	19	1.5%
110	7	0.5%
128	7	0.5%
132	2	0.2%
133	1	0.1%
135	2	0.2%

Value	Count	Frequency (%)
1761	2	0.2%
1702	2	0.2%
1400	3	0.2%
1050	1	0.1%
1025	4	0.3%
981	4	0.3%
909	6	0.5%
825	2	0.2%
770	1	0.1%
759	1	0.1%

Diesel
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	10.1 KiB

0	692
1	582

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1274
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	692	54.3%
1	582	45.7%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	692	54.3%
1	582	45.7%

Most occurring characters

Value	Count	Frequency (%)
0	692	54.3%
1	582	45.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1274	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	692	54.3%
1	582	45.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	1274	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	692	54.3%
1	582	45.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1274	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	692	54.3%
1	582	45.7%

CNG
Categorical

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	10.1 KiB

0	1252
1	22

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1274
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	1252	98.3%
1	22	1.7%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	1252	98.3%
1	22	1.7%

Most occurring characters

Value	Count	Frequency (%)
0	1252	98.3%
1	22	1.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1274	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1252	98.3%
1	22	1.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	1274	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	1252	98.3%
1	22	1.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1274	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	1252	98.3%
1	22	1.7%

Petrol
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	10.1 KiB

1	648
0	626

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1274
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	648	50.9%
0	626	49.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	648	50.9%
0	626	49.1%

Most occurring characters

Value	Count	Frequency (%)
1	648	50.9%
0	626	49.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1274	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	648	50.9%
0	626	49.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	1274	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	648	50.9%
0	626	49.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1274	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	648	50.9%
0	626	49.1%

Electric
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	10.1 KiB

0	1261
1	13

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1274
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	1261	99.0%
1	13	1.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	1261	99.0%
1	13	1.0%

Most occurring characters

Value	Count	Frequency (%)
0	1261	99.0%
1	13	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1274	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1261	99.0%
1	13	1.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1274	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	1261	99.0%
1	13	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1274	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	1261	99.0%
1	13	1.0%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Ex-Showroom_Price	Displacement	Cylinders	Valves_Per_Cylinder	Fuel_Tank_Capacity	Height	Length	Width	Doors	City_Mileage	Gears	Seating_Capacity	Basic_Warranty	Boot_Space	CNG	Petrol
0	292667	624.0	2.0	2.0	24.0	1652.0	3164.0	1750.0	5.0	NaN	4.0	4.0	2.0	110.0	0	1
1	236447	624.0	2.0	2.0	24.0	1652.0	3164.0	1750.0	5.0	NaN	4.0	4.0	2.0	110.0	0	1
2	296661	624.0	2.0	2.0	15.0	1652.0	3164.0	1750.0	4.0	NaN	4.0	4.0	2.0	110.0	1	0
3	334768	624.0	2.0	2.0	24.0	1652.0	3164.0	1750.0	5.0	NaN	5.0	4.0	2.0	94.0	0	1
4	272223	624.0	2.0	2.0	24.0	1652.0	3164.0	1750.0	5.0	NaN	4.0	4.0	2.0	110.0	0	1
5	314815	624.0	2.0	2.0	24.0	1652.0	3164.0	1750.0	5.0	NaN	5.0	4.0	2.0	94.0	0	1
6	279650	799.0	3.0	4.0	28.0	1541.0	3429.0	1560.0	5.0	NaN	5.0	5.0	2.0	222.0	0	1
7	351832	799.0	3.0	4.0	28.0	1541.0	3429.0	1560.0	5.0	NaN	5.0	5.0	2.0	222.0	0	1
8	333419	799.0	3.0	4.0	28.0	1541.0	3429.0	1560.0	5.0	NaN	5.0	5.0	2.0	222.0	0	1
9	362000	799.0	3.0	4.0	28.0	1541.0	3429.0	1560.0	5.0	NaN	5.0	5.0	2.0	222.0	0	1

Last rows

	Ex-Showroom_Price	Displacement	Cylinders	Valves_Per_Cylinder	Fuel_Tank_Capacity	Height	Length	Width	Doors	City_Mileage	Gears	Seating_Capacity	Basic_Warranty	Boot_Space	Diesel	Petrol
1264	1065900	1497.0	4.0	4.0	40.0	1495.0	4440.0	1695.0	4.0	NaN	5.0	5.0	2.0	510.0	0	1
1265	1182000	1497.0	4.0	4.0	40.0	1495.0	4440.0	1695.0	4.0	NaN	5.0	5.0	2.0	510.0	0	1
1266	1312000	1497.0	4.0	4.0	40.0	1495.0	4440.0	1695.0	4.0	NaN	5.0	5.0	2.0	510.0	0	1
1267	1111000	1498.0	4.0	4.0	40.0	1495.0	4440.0	1695.0	4.0	NaN	6.0	5.0	2.0	510.0	1	0
1268	1191000	1498.0	4.0	4.0	40.0	1495.0	4440.0	1695.0	4.0	NaN	6.0	5.0	2.0	510.0	1	0
1269	1302000	1498.0	4.0	4.0	40.0	1495.0	4440.0	1695.0	4.0	NaN	6.0	5.0	2.0	510.0	1	0
1270	1421000	1498.0	4.0	4.0	40.0	1495.0	4440.0	1695.0	4.0	NaN	6.0	5.0	2.0	510.0	1	0
1271	1431000	1497.0	4.0	4.0	40.0	1495.0	4440.0	1695.0	4.0	NaN	5.0	5.0	2.0	510.0	0	1
1272	1201000	1497.0	4.0	4.0	40.0	1495.0	4440.0	1695.0	4.0	NaN	5.0	5.0	2.0	510.0	0	1
1273	6862560	3200.0	4.0	4.0	88.0	1900.0	4900.0	1875.0	5.0	NaN	5.0	7.0	NaN	1050.0	1	0

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks